Infinite Observations


Wladimir Kruythoff

Wladimir Kruythoff

Founder & CEO Infinite Observations

Forecasting The 2020 Hurricane Season Using ZineQx From Infinite Observations

On Wednesday, August 5th 2020, the Colorado State University (CSU) research team — the standard-bearer for seasonal hurricane forecasts —  released the most extreme forecast in the institution’s 37-year history for the 2020 hurricane season. 

“Extremely active” was the term used by CSU to label the 2020 hurricane season. The CSU team predicts 24 named storms of which 12 are hurricanes and five of these predicted as major hurricanes. These figures are double the number projected for a regular season. If these numbers turn out to be accurate, 2020 will be the second most active Atlantic hurricane season, second only to 2005, which produced Hurricanes Katrina and Wilma.

Infinite Observation will closely monitor this active hurricane season using its in-house developed ZineQx cloud application.  This powerful disaster assessment & risk management platform integrates macro-economic indicators with Big Data, machine learning and GIS databases to forecast damage levels and make disaster risk assessments of the impact of the hurricanes long before landfall. ZineQx can make similar predictions and assessments for floodings and other natural and man-made disasters.

A risk-based asset management information system, ZineQx uses Failure Mode, Effects & Criticality Analyses (FMECA) which has a bottom-up (detailed) or top-down (functional) approach to risk analysis and assessments. In addition, ZineQx is inductive, meaning data-driven, and the information derived from this system can be technical, practical, and informative. 

Data can be inputted by on-site collection (in the field from experts, drones, etc.), or it can be inputted online (collected from a digital database or paper-based documentation).  All input data and output results must be reliable and validated; this is one of the most critical steps in the process. ZineQx data is stored in NoSQL databases as simple features or simple feature access, which refers to a formal standard (ISO 19125-1:2004) that describes how real-world objects can be represented in computers, emphasizing the spatial geometry of these objects. This standard is universally implemented in spatial databases (SDB, such as PostGIS) and spatial data frame (SDF) format and can be exported to other geographic information systems (GIS) applications such as  ESRI ArcGIS and QGIS. A subset of simple features forms the GeoJSON standard. TopoJSON is subsequently an extension of  GeoJSON, a specific form of the JSON file format. Dataframes are read from many sources, such as shapefiles, feature classes, GeoJSON, and Feature Layers.

The ZineQx application decomposes the elements in an object or multiple objects forming a system and links the elements of that object or system, thus creating a relationship or (a) chain(s). By determining the effect(s) of failure, the failure mode(s), and the cause(s) or mechanism(s) of failure, ZineQx can give a reliable analysis of the life cycle of an individual element, object(s), a composition of elements, and the system in its entirety. The ZineQx methodology is comparable to the steps of the Root Cause Analysis (RCA) technique. During the Analyze phase of the Define, Measure, Analyze, Improve and Control (DMAIC) process and the Plan phase of Plan-Do-Check-Act (PDCA) activities, these steps the basis.

Each object in ZineQx has failure modes, each failure mode has a probability assigned to each cause, and each cause has a failure rate. If no failure data is available for an object, then the probability of occurrence will be assigned to elements of that object. The likelihood of failure of elements depends on the failure data that is exploited in the ZineQx analyses. ZineQx analyses, like FMECA, can be performed far in advance or shortly before any event or occurrence that initiates the failure of an element, object, or system. In other words, ZineQx simulations are predictive and measured by criticality, which is a product of numerous factors, most notably of course severity and probability. These predictions provide an opportunity to take action and reduce the level of exposure or even avoid the failure of an element, object, or entire system.

In the case of a nation faced with natural disaster, this would mean ensuring that the Effect of Failure, represented by the negative experience of consumers and enterprises, is translated into a Failure Mode or a technical description of failure by ZineQx. With ZineQx, the user (consumer or enterprise) is offered a complete overview of the assets to be maintained. Oversight, priority, and budget play crucial roles for other clients (larger companies or governments) managing and maintaining multiple assets (whole regions or a nation). ZineQx gives the user the flexibility to prioritize assets based on their integrity or probability of failure during an extreme event and budget the costs of upgrades.

The advantages of using ZineQx are
(1) Localization (of an element, the object, or an entire system) but also the cause and probability of failure.
(2)  Scientific (quantifiable data)
(3) Verification (the analyses are based on standard norms, codes, regulations, guidelines, etc.)
(4) Reporting (all in- and output can be presented and organized in tables, graphs, images and other visualization for clear interpretation by all parties involved in the process).
Data can be enhanced by adding recurring inspection results or can be expanded by adding new/additional data over time to improve the simulations, visualizations, reporting as well as budget plans.

For more information, please visit Infinite Observation.

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